# Key Features

## Scalability at Global Scale

Dekuper supports adding millions of GPU-enabled nodes, dynamically scaling compute power as demand grows. Unlike traditional platforms, this decentralized model eliminates bottlenecks caused by centralized infrastructure constraints.

## Enhanced Cost-Effectiveness

By leveraging unused GPU resources, Dekuper significantly reduces the cost of AI model training, fine-tuning, and inference. This efficiency empowers startups, researchers, and small businesses to access high-performance computing (HPC) capabilities without breaking the bank.

## Superior Efficiency for LLM Workloads

Dekuper’s architecture delivers up to 30% greater efficiency in training and fine-tuning large language models (LLMs), thanks to optimized workload distribution and GPU utilization. This advantage translates into faster development cycles and improved AI model performance.

## Green Computing

Dekuper minimizes the need for energy-intensive data centers by repurposing existing GPU resources, contributing to a more sustainable computing environment. This eco-friendly model aligns with global efforts to reduce carbon footprints.

## Decentralized Security

Security is built into the fabric of Dekuper’s peer-to-peer architecture. Distributed consensus mechanisms and advanced encryption ensure that data integrity and privacy are maintained without reliance on a single point of failure.
